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If you live in or near Toronto, are interested in learning about data science, and can spare Friday afternoons, then you are in luck. I am offering a Data Science Boot Camp at Ryerson University in collaboration with IBM’s BigDataUniversity.com.
The Boot Camp is largely based on the contents of my recently published book, Getting Started with Data Science: Making Sense of Data with Analytics. You can read more about the book by Clicking HERE.
Where: 55 Dundas Street West, Toronto, 9th floor, Room 3-109
Ted Rogers School of Management, Ryerson University
Cost: Free (Courtesy Ryerson University & BigDataUniversity)
Starting on: May 13 for introductions. Actual launch is on May 20.
Spaces: I’d like to cap enrollment at 15.
Registration: Email us or use Registration Form at BigDataUniversity.
Prerequisites: Curiosity, high-school math, prescribed book, a laptop computer, and willingness to learn R.
BigDataUniversity will live stream the sessions for those who are unable to attend, but interested in the topic.
Week 2 – Data: It’s shapes, sizes, and formats
Week 3 – Regression: The tool that fixes everything, or almost everything.
Week 5 – Aerobics with data: Taming your data to meet your needs.
Week 6 – Time is money: Analytics with time series data.
Week 7 – Case study 1:
The Boot Camp is largely based on the contents of my recently published book, Getting Started with Data Science: Making Sense of Data with Analytics. You can read more about the book by Clicking HERE.
Logistical details:
When: Fridays (2:00 – 5:00 pm)Where: 55 Dundas Street West, Toronto, 9th floor, Room 3-109
Ted Rogers School of Management, Ryerson University
Cost: Free (Courtesy Ryerson University & BigDataUniversity)
Starting on: May 13 for introductions. Actual launch is on May 20.
Spaces: I’d like to cap enrollment at 15.
Registration: Email us or use Registration Form at BigDataUniversity.
Prerequisites: Curiosity, high-school math, prescribed book, a laptop computer, and willingness to learn R.
BigDataUniversity will live stream the sessions for those who are unable to attend, but interested in the topic.
Tentative Schedule
May 13, 2016– Introductions, software details, and logistical details.
Week 1 – Taking the first step
- Detailed hands-on examples of analytics to understand what you will be able to accomplish by the end of the boot camp.
Week 3 – Regression: The tool that fixes everything, or almost everything.
- Applied analytics with teaching evaluations.
- Do good-looking instructors get higher teaching evaluations?
Week 5 – Aerobics with data: Taming your data to meet your needs.
Week 6 – Time is money: Analytics with time series data.
Week 7 – Case study 1:
- Do women who lack health insurance from their spouse’s employer more likely to work full-time?
- Do higher taxes result in lower cigarette sales? Did Land Transfer Tax impact housing sales in Toronto?
- To smoke or not to smoke: that is the question.
- Is space the new frontier? Map it to know it.
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